Queue-based agent communication architecture for intelligent human-like computer interfaces

Human-like computer interaction systems requires far more than just simple speech input/output. Such a system should communicate with the user verbally, using a conversational style language. It should be aware of its surroundings and use this context for any decisions it makes. As a synthetic character, it should have a computer generated human-like appearance. This, in turn, should be used to convey emotions, expressions and gestures. Finally, and perhaps most important of all, the system should interact with the user in real time, in a fluent and believable manner.

Human-computer cooperative teleoperation with time delay

Presents a method for model based bilateral control of master-slave arm with time delay between master and slave arms, where the system supports cooperative action between manual and automatic modes. The method realises efficiencies in master-slave arm control with the simplicities of a computer and the flexibility of a skilled human operator.

Practical neural networks in a computer control package

This paper deals with the integration of radial basis function (RBF) networks into the industrial software control package Connoisseur. The paper shows the improved modelling capabilities offered by RBF networks within the Connoisseur environment compared to linear modelling techniques such as recursive least squares. The paper also goes on to mention the way this improved modelling capability, obtained through the RBF networks will be utilised within Connoisseur.

Computer-mediated communication in distance MA programmes: the student's perspective

This paper reports on a study of computer-mediated communication within the context of a distance MA in TEFL programme which used an e-mail discussion list and then a discussion board. The study focused on the computer/Internet access and skills of the target population and their CMC needs and wants. Data were collected from 63 questionnaires and 6 in-depth interviews with students. Findings indicate that computer use and access to the Internet are widespread within the target population. In addition, most respondents indicated some competence in Internet use. No single factor emerged as an overriding inhibiting factor for lack of personal use. There was limited use of the CMC tools provided on the course for student–student interaction, mainly attributable to time constraints. However, most respondents said that they would like more CMC interaction with tutors. The main factor which would contribute to greater Internet use was training. The paper concludes with recommendations and suggestions for learner training in this area.

Brain computer interface control via functional connectivity dynamics

The dynamics of inter-regional communication within the brain during cognitive processing – referred to as functional connectivity – are investigated as a control feature for a brain computer interface. EMDPL is used to map phase synchronization levels between all channel pair combinations in the EEG. This results in complex networks of channel connectivity at all time–frequency locations. The mean clustering coefficient is then used as a descriptive feature encapsulating information about inter-channel connectivity. Hidden Markov models are applied to characterize and classify dynamics of the resulting complex networks. Highly accurate levels of classification are achieved when this technique is applied to classify EEG recorded during real and imagined single finger taps. These results are compared to traditional features used in the classification of a finger tap BCI demonstrating that functional connectivity dynamics provide additional information and improved BCI control accuracies.

Investigating familiar interfaces to help older adults learn computer applications more easily

Many older adults wish to gain competence in using a computer, but many application interfaces are perceived as complex and difficult to use, deterring potential users from investing the time to learn them. Hence, this study looks at the potential of ‘familiar’ interface design which builds upon users’ knowledge of real world interactions, and applies existing skills to a new domain. Tools are provided in the form of familiar visual objects, and manipulated like real-world counterparts, rather than with buttons, icons and menus found in classic WIMP interfaces. This paper describes the formative evaluation of computer interactions that are based upon familiar real world tasks, which supports multitouch interaction, involves few buttons and icons, no menus, no right-clicks or double-clicks and no dialogs. Using an example of an email client to test the principles of using “familiarity”, the initial feedback was very encouraging, with 3 of the 4 participants being able to undertake some of the basic email tasks with no prior training and little or no help. The feedback has informed a number of refinements of the design principles, such as providing clearer affordance for visual objects. A full study is currently underway.

Computer vision and color measurement techniques for inline monitoring of cheese curd syneresis

Optical characteristics of stirred curd were simultaneously monitored during syneresis in a 10-L cheese vat using computer vision and colorimetric measurements. Curd syneresis kinetic conditions were varied using 2 levels of milk pH (6.0 and 6.5) and 2 agitation speeds (12.1 and 27.2 rpm). Measured optical parameters were compared with gravimetric measurements of syneresis, taken simultaneously. The results showed that computer vision and colorimeter measurements have potential for monitoring syneresis. The 2 different phases, curd and whey, were distinguished by means of color differences. As syneresis progressed, the backscattered light became increasingly yellow in hue for circa 20 min for the higher stirring speed and circa 30 min for the lower stirring speed. Syneresis-related gravimetric measurements of importance to cheese making (e.g., curd moisture content, total solids in whey, and yield of whey) correlated significantly with computer vision and colorimetric measurements..

Correlation between process cheese meltability determined by sensory analysis, computer vision method and Olson and Price test

The meltabilities of 14 process cheese samples were determined at 2 and 4 weeks after manufacture using sensory analysis, a computer vision method, and the Olson and Price test. Sensory analysis meltability correlated with both computer vision meltability (R-2 = 0.71, P < 0.001) and Olson and Price meltability (R-2 = 0.69, P < 0.001). There was a marked lack of correlation between the computer vision method and the Olson and Price test. This study showed that the Olson and Price test gave greater repeatability than the computer vision method. Results showed process cheese meltability decreased with increasing inorganic salt content and with lower moisture/fat ratios. There was very little evidence in this study to show that process cheese meltability changed between 2 and 4 weeks after manufacture..

Low cost brain-computer interface: first results

Brain-Computer Interfacing (BCI) has been previously demonstrated to restore patient communication, meeting with varying degrees of success. Due to the nature of the equipment traditionally used in BCI experimentation (the electroencephalograph) it is mostly conned to clinical and research environments. The required medical safety standards, subsequent cost of equipment and its application/training times are all issues that need to be resolved if BCIs are to be taken out of the lab/clinic and delivered to the home market. The results in this paper demonstrate a system developed with a low cost medical grade EEG amplier unit in conjunction with the open source BCI2000 software suite thus constructing the cheapest per electrode system available, meeting rigorous clinical safety standards. Discussion of the future of this technology and future work concerning this platform are also introduced.